AWS Big Data

JANUARY 15, 2025

This agility accelerates EUROGATEs insight generation, keeping decision-making aligned with current data. Additionally, daily ETL transformations through AWS Glue ensure high-quality, structured data for ML, enabling efficient model training and predictive analytics.

IoT 100

IoT Machine Learning Metadata Data-driven 100

Smart Data Collective

JULY 1, 2023

The resulting structured data is then used to train a machine learning algorithm. Consistency and agreement Establish an agreement metric (e.g., Review annotated data Have a separate team review the annotated data for quality control. This will reduce inconsistencies and errors in annotations.

Machine Learning 93

Machine Learning Metrics Uncertainty Deep Learning 93

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. Grant the user role permissions for sensitive information and compliance policies.

Data Governance 109

Data Governance Unstructured Data Metadata Data Lake 109

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes.

Management 80

Management Metrics Data Processing Data Lake 80

Analytics Vidhya

SEPTEMBER 3, 2020

Overview Precision and recall are two crucial yet misunderstood topics in machine learning We’ll discuss what precision and recall are, how they work, and. The post Precision vs. Recall – An Intuitive Guide for Every Machine Learning Person appeared first on Analytics Vidhya.

Machine Learning 304

Machine Learning Analytics Metrics Structured Data 304

AWS Big Data

APRIL 2, 2024

Our evaluation mechanisms can be summarized as follows: Tracking automated metrics for quality assessment – We tracked a combination of more than 10 supervised and unsupervised metrics to evaluate essential quality factors such as informativeness, conciseness, reliability, semantic coverage, coherence, and cohesiveness.

Metadata 101

Metadata Metrics Data-driven Contextual Data 101

AWS Big Data

AUGUST 15, 2024

To learn more, see Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions. In this post, we show how to capture the data quality metrics for data assets produced in Amazon Redshift. Amazon DataZone natively supports data sharing for Amazon Redshift data assets.

Data Quality 106

Data Quality Visualization Metadata Key Performance Indicator 106

AWS Big Data

MARCH 2, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to use SQL for analyzing structured and semi-structured data with best price performance along with secure access to the data.

Visualization 86

Visualization Dashboards Data Warehouse Metrics 86

Ontotext

OCTOBER 14, 2021

Investment firms, including one of Ontotext’s clients, spend enormous sums every year buying data from brokers, while also producing original analyses and relying on coverage from news media, especially in regions where raw numbers are harder to find. See figure 1.). Mock Knowledge Graph for New Delhi Ventures.

Reporting 98

Reporting Structured Data Data Warehouse Metadata 98

Octopai

FEBRUARY 8, 2020

The two teams (Lockheed Martin and NASA Jet Propulsion Laboratory) that built the thrusters miscommunicated units (English to metric). Unfortunately, these errors were not caught until too late, for example: 1. So, the software miscalculated. They ignored all the warning signs.

Metadata 90

Metadata Key Performance Indicator Unstructured Data Business Intelligence 90

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Complete the implementation tasks such as data ingestion and performance testing.

Testing 109

Testing Data Warehouse Metrics Cost-Benefit 109

IBM Big Data Hub

APRIL 9, 2024

Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications. “Being able to organize the data around that structure helps us to efficiently query, retrieve and use the information downstream, for example for AI narration.”

Management 78

Management IT Machine Learning Metrics 78

AWS Big Data

OCTOBER 2, 2023

The function JSON_PARSE allows you to extract the binary data in the stream and convert it into the SUPER data type. With the SUPER data type and PartiQL language, Amazon Redshift extends its capabilities for semi-structured data analysis.

Cost-Benefit 99

Cost-Benefit Metadata Structured Data Data-driven 99

Sisense

JUNE 8, 2020

“This ability to pull data sets together from a cloud-native environment for better transparency and faster decision making, in turn, can give analysts the speed they need to answer questions quickly and more accurately with more data collaboration,” Lee added. Deeper insights from bigger data sets.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

IBM Big Data Hub

NOVEMBER 29, 2023

Furthermore, AI algorithms’ capacity for recognizing patterns—by learning from your company’s unique historical data—can empower businesses to predict new trends and spot anomalies sooner and with low latency.

Unstructured Data 84

Unstructured Data Data-driven ROI Machine Learning 84

AWS Big Data

MARCH 7, 2023

You can use simple SQL to analyze structured and semi-structured data across data warehouses, data marts, operational databases, and data lakes to deliver the best price performance at any scale. Data in Amazon S3 can be easily queried in place using SQL with Amazon Redshift Spectrum.

Analytics 78

Analytics Data Warehouse Data Lake Metadata 78

AWS Big Data

MARCH 25, 2024

Stream processing, however, can enable the chatbot to access real-time data and adapt to changes in availability and price, providing the best guidance to the customer and enhancing the customer experience. When the model finds an anomaly or abnormal metric value, it should immediately produce an alert and notify the operator.

Data Lake 104

Data Lake Unstructured Data Management Snapshot 104

Alation

FEBRUARY 20, 2020

By changing the cost structure of collecting data, it increased the volume of data stored in every organization. Additionally, Hadoop removed the requirement to model or structure data when writing to a physical store.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

AWS Big Data

NOVEMBER 9, 2023

Third-party APIs – These provide analytics and survey data related to ecommerce websites. This could include details like traffic metrics, user behavior, conversion rates, customer feedback, and more. Flat files – Other systems supply data in the form of flat files of different formats.

Data Warehouse 118

Data Warehouse Testing Data Quality Reporting 118

Ontotext

JUNE 22, 2023

All derived facts can be further put into context with structured data, which improves data quality and presents researchers with clear evidence and provenance for all insights Then, Ontotext’s Target Discovery provides deeper insights into the data stored in this highly-interlinked knowledge graph, where long sequences of relations can be mined.

Metrics 52

Metrics Statistics Visualization Data-driven 52

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

AWS Big Data

DECEMBER 21, 2023

For the downstream consumption by all departments across the organization, smava’s Data Platform team prepares curated data products following the extract, load, and transform (ELT) pattern. Future vision For the future, smava plans to continue to optimize the Data Platform based on operational metrics.

Data Lake 103

Data Lake Data Warehouse Data-driven B2B 103

CIO Business Intelligence

JUNE 14, 2023

In the case of intelligent operations, real-time data informs immediate operational decisions. An airline carrier needs to know how many gates are open and how many passengers are on each plane – metrics that change from moment to moment. Consider data types.

Unstructured Data 64

Unstructured Data IT Manufacturing Visualization 64

Jet Global

FEBRUARY 18, 2020

People often forget his next statement: “90 percent of all that new data is unstructured.” So if we think historically about companies with an ERP, they’re typically using structured data (strictly defined and classified), and they’re not very proactive about pushing insights toward users.

Data-driven 64

Data-driven Machine Learning Cost-Benefit ROI 64

CIO Business Intelligence

DECEMBER 4, 2023

Once focused solely on reducing search and retrieval times, information lifecycle management (ILM) is now critical to workflow automation, identifying and tracking performance metrics, and harnessing the burgeoning potential of AI. Operationalizing data to drive revenue CIOs report that their roles are rising in importance and impact.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

FineReport

APRIL 11, 2023

Free Download of FineReport What is Business Intelligence Dashboard (BI Dashboard)？ A business intelligence dashboard, also known as a BI dashboard, is a tool that presents important business metrics and data points in a visual and analytical format on a single screen.

Dashboards 40

Dashboards Business Intelligence Metrics Cost-Benefit 40

AWS Big Data

FEBRUARY 22, 2023

Data analytic challenges As an ecommerce company, Ruparupa produces a lot of data from their ecommerce website, their inventory systems, and distribution and finance applications. The data can be structured data from existing systems, and can also be unstructured or semi-structured data from their customer interactions.

Data Lake 52

Data Lake Dashboards Cost-Benefit Data Warehouse 52

Alation

JULY 19, 2022

Historically restricted to the purview of data engineers, data quality information is essential for all user groups to see. Finally, data catalogs can help data scientists promulgate the results of their projects. Data scientists often have different requirements for a data catalog than data analysts.

Metadata 59

Metadata Data Quality Statistics Data Science 59

AWS Big Data

JANUARY 22, 2024

The success of the implementation meant assessing various aspects of the data infrastructure, data management, and business outcomes. They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers.

Data-driven 99

Data-driven Advertising Metadata Data Architecture 99

Domino Data Lab

MARCH 3, 2019

What metrics are used to evaluate success? There are essentially four types encountered: image/video, audio, text, and structured data. What’s been the impact of using ML models on culture and organization? Who builds their models? How are decisions and priorities set and by whom within the organization?

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Cloudera

DECEMBER 15, 2017

Manufacturing can move from working with approximations to insight based on actual data, as it happens. Overall performance would be improved through better forecasts of product demand and production, through the understanding of plant operations across multiple metrics, and by being able to provide service and support to customers faster.

Manufacturing 40

Manufacturing Machine Learning IoT Data-driven 40

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. With this capability, you can design reports for different levels catering to varying needs: executive reports offering strategic overviews, management reports highlighting operational metrics, and detailed reports diving into the specifics.

Data Strategy 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

AWS Big Data

FEBRUARY 26, 2025

It enables in-order reads during stream scale-up or scale-down, supports Flinks native watermarking, and improves observability through unified connector metrics. You can use the new connector to read data from a Kinesis data stream starting with Flink version 1.19. and provides several enhancements.

Analytics 59

Analytics Data Lake Metadata Data Warehouse 59

Wayne Yaddow

FEBRUARY 26, 2025

AI-powered parsing models detect complex format inconsistencies across structured and semi-structured data. Real-World Example A senior data engineer at a SaaS company leverages an AI-powered format validation tool to ensure that CSV-to-JSON conversions preserve numeric precision.

Data Transformation 52

Data Transformation Testing Data-driven Data Quality 52

FineReport

MARCH 7, 2024

Data Acquisition I categorize data sources into three types: (1) First-party data: User factual data, such as financial products purchased at a certain institution, time of purchase, issuing branch, name, phone number, or operational data, such as user behavioral data on a financial app. (2)

Dashboards 52

Dashboards Reporting Advertising Statistics 52

Alation

OCTOBER 28, 2021

To make good on this potential, healthcare organizations need to understand their data and how they can use it. This means establishing and enforcing policies and processes, standards, roles, and metrics. Why Is Data Governance in Healthcare Important? Data governance is the solution to these challenges.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52